Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting

被引:74
作者
Ahn, Jae Joon [1 ]
Byun, Hyun Woo [1 ]
Oh, Kyong Joo [1 ]
Kim, Tae Yoon [2 ]
机构
[1] Yonsei Univ, Dept Informat & Ind Engn, Seoul 120749, South Korea
[2] Keimyung Univ, Dept Stat, Taegu 704701, South Korea
基金
新加坡国家研究基金会;
关键词
Ridge regression; Genetic algorithm; Real estate market; NEURAL-NETWORKS; SUPPORT; PREDICTION; SYSTEM;
D O I
10.1016/j.eswa.2012.01.183
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study considers real estate appraisal forecasting problem. While there is a great deal of literature about use of artificial intelligence and multiple linear regression for the problem, there has been always controversy about which one performs better. Noting that this controversy is due to difficulty finding proper predictor variables in real estate appraisal, we propose a modified version of ridge regression, i.e., ridge regression coupled with genetic algorithm (GA-Ridge). In order to examine the performance of the proposed method, experimental study is done for Korean real estate market, which verifies that GA-Ridge is effective in forecasting real estate appraisal. This study addresses two critical issues regarding the use of ridge regression, i.e., when to use it and how to improve it. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:8369 / 8379
页数:11
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